Spoiler Detection

Spoiler detection research aims to automatically identify text containing spoilers, primarily in online movie reviews and clickbait headlines, improving user experience and content curation. Current approaches leverage various machine learning models, including transformer architectures and multi-modal networks that integrate text, metadata, and user network data to enhance accuracy and robustness across different domains and spoiler types. This work is significant for improving online content filtering and personalization, and contributes to the broader field of natural language processing by advancing techniques in text classification, generation, and knowledge integration.